A unified framework for interactive visual graph matching via attribute-structure synchronization

IF 2.8 4区 计算机科学 Q2 COMPUTER SCIENCE, SOFTWARE ENGINEERING
Yuhua Liu , Haoxuan Wang , Jiajia Kou , Ling Sun , Heyu Wang , Yongheng Wang , Yigang Wang , Jinchang Li , Zhiguang Zhou
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引用次数: 0

Abstract

In traditional graph retrieval tools, graph matching is commonly used to retrieve desired graphs from extensive graph datasets according to their structural similarities. However, in real applications, graph nodes have numerous attributes which also contain valuable information for evaluating similarities between graphs. Thus, to achieve superior graph matching results, it is crucial for graph retrieval tools to make full use of the attribute information in addition to structural information. We propose a novel framework for interactive visual graph matching. In the proposed framework, an attribute-structure synchronization method is developed for representing structural and attribute features in a unified embedding space based on Canonical Correlation Analysis (CCA). To support fast and interactive matching, our method provides users with intuitive visual query interfaces for traversing, filtering and searching for the target graph in the embedding space conveniently. With the designed interfaces, the users can also specify a new target graph with desired structural and semantic features. Besides, evaluation views are designed for easy validation and interpretation of the matching results. Case studies and quantitative comparisons on real-world datasets have demonstrated the superiorities of our proposed framework in graph matching and large graph exploration.

Abstract Image

基于属性-结构同步的交互式可视化图形匹配统一框架
在传统的图检索工具中,图匹配通常是根据图的结构相似度从大量的图数据集中检索所需的图。然而,在实际应用中,图节点具有许多属性,这些属性还包含有价值的信息,用于评估图之间的相似性。因此,为了获得更好的图匹配结果,图检索工具除了充分利用结构信息外,还必须充分利用属性信息。我们提出了一种新的交互式视觉图形匹配框架。在该框架中,提出了一种基于典型相关分析(CCA)的属性-结构同步方法,用于在统一嵌入空间中表示结构和属性特征。为了支持快速和交互式匹配,我们的方法为用户提供了直观的可视化查询界面,方便用户在嵌入空间中遍历、过滤和搜索目标图。通过设计的接口,用户还可以指定具有所需结构和语义特征的新目标图。此外,还设计了评价视图,便于对匹配结果进行验证和解释。案例研究和对真实世界数据集的定量比较证明了我们提出的框架在图匹配和大图探索方面的优势。
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来源期刊
Computers & Graphics-Uk
Computers & Graphics-Uk 工程技术-计算机:软件工程
CiteScore
5.30
自引率
12.00%
发文量
173
审稿时长
38 days
期刊介绍: Computers & Graphics is dedicated to disseminate information on research and applications of computer graphics (CG) techniques. The journal encourages articles on: 1. Research and applications of interactive computer graphics. We are particularly interested in novel interaction techniques and applications of CG to problem domains. 2. State-of-the-art papers on late-breaking, cutting-edge research on CG. 3. Information on innovative uses of graphics principles and technologies. 4. Tutorial papers on both teaching CG principles and innovative uses of CG in education.
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